Systems and methods for providing automatic enabling and disabling of wireless communications for user equipment

ABSTRACT

A user equipment (“UE”) described herein may use automated techniques to receive one or more mode triggers, each including one or more sensor profiles. The UE may monitor data from one or more sensors associated with the UE and may compare the data to the profiles. The UE may determine that the sensor data matches a profile; and may disable one or more wireless features. The UE may continue to monitor sensor data and may determine that an exit trigger condition has been satisfied based on the received data. The exit trigger condition may specify a particular mode trigger; and a set of exit sensor profiles that corresponds to an exit of the particular mode trigger. The UE may, based on determining that the exit trigger condition has been satisfied, activate one or more wireless features. The sensor profiles and/or exit trigger conditions may be received from a cloud-based entity.

CROSS-REFERENCE TO RELATED APPLICATION

This Application is a Continuation of U.S. patent application Ser. No.16/780,097, flied on Feb. 3, 2020, titled “SYSTEMS AND METHODS FORPROVIDING AUTOMATIC ENABLING AND DISABLING OF WIRELESS COMMUNICATIONSFOR USER EQUIPMENT,” the contents of which are herein incorporated byreference in their entirety.

BACKGROUND

Use of various electronic device features, such as radio communicationelements of User Equipment (“UE”) such as mobile telephones, tabletdevices, laptops, or the like, may be prohibited during airplane travelor transport, or portions thereof (e.g., takeoff and/or landing).

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates the utilization of machine learning techniques togenerate and use triggers to provide automatic activation and/ordeactivation of wireless communications associated with a UE, inaccordance with embodiments described herein;

FIG. 2 illustrates an example environment in which one or moreembodiments, described herein, may be implemented;

FIG. 3 illustrates an example process by which communication modetriggers may be generated based on itinerary information;

FIG. 4 illustrates an example process by which UE information ismonitored and compared to communication mode triggers to identifytrigger events;

FIG. 5 illustrates an example process by which UE information ismonitored locally when wireless communications are disabled and comparedto communication mode exit triggers to identify trigger events;

FIG. 6 illustrates an example process by which machine learning isapplied to event history and used to update event trigger definitions;and

FIG. 7 illustrates example components of one or more devices, accordingto one or more embodiments described herein.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

The following detailed description refers to the accompanying drawings.The same reference numbers in different drawings may identify the sameor similar elements.

Embodiments described herein provide techniques for selectively enablingor disabling wireless communications of a User Equipment (“UE”) based ontrigger events using location and/or other sensing capabilities of theUE. Some embodiments may use machine learning and/or other techniques todetermine or refine the determination of when such events occur, thusenhancing the reliability of the determination of when UEs should enableor disable wireless communication features.

One such example of enabling or disabling wireless communicationfeatures is an “airplane mode” feature. In accordance with someembodiments, the airplane mode feature may be activated or deactivatedduring takeoff and/or landing of an aircraft, and/or at some othersuitable time. Enabling and/or disabling wireless communication features(e.g., enabling and/or disabling airplane mode) may include, forinstance, enabling and/or disabling global positioning system (“GPS”)position sensors, cellular transmitters and/or receivers, and/or otherwireless communication circuitry and/or logic (e.g., Bluetooth, Wi-Fi,etc.).

FIG. 1 illustrates the utilization of machine learning to generate anduse triggers to provide automatic activation and/or deactivation ofwireless communications associated with a UE, in accordance withembodiments described herein. As shown, a mode manager 110 (e.g., one ormore devices) may collect UE information, itinerary or shipmentinformation, location or geographic information, airport information,and/or other information relevant to the determination of whether agiven UE should enable or disable its wireless communications.

The UE information may include identifying information related to UE 120(e.g., an identifier of UE 120, such as an International MobileSubscriber Identity (“IMSI”), an International Mobile Station EquipmentIdentity (“IMEI”), an Mobile Directory Number (“MDN”), and/or some otheridentifier), UE location information (e.g., location informationdetermined by UE 120, such as using a GPS technique, and/or locationinformation determined by a wireless network, such as using atriangulation technique), and/or other relevant information related toUE 120. The UE information may be received from UE 120, a storageassociated with mode manager 110, and/or various network-accessibleresources (e.g., an Home Subscriber Server (“HSS”), a Unified DataManagement function (“UDM”), and/or other devices or systems associatedwith a wireless network with which UE 120 is associated).

The itinerary information may include information regarding a scheduledtravel route associated with UE 120, such as origin, destination,intermediate stops, departure time(s), arrival time(s), expected transittime(s), etc. Location information may be provided at various levels ofgranularity. For instance, an origin or destination may include a regionor city, airport, terminal, specific plane, latitude and longitudecoordinates, or some other representation of location.

Itinerary information may be received from various appropriateresources. For instance, in some embodiments, itinerary information fora particular UE 120 may be provided by UE 120. As another example, acarrier server or other such resource may provide itinerary informationvia an application programming interface (“API”), web-based resource,and/or other appropriate resources available to UE 120 (e.g., an updatemessage service where mode manager 110 may distribute informationupdates to some or all UEs 120 by exchanging a set of update messageswith UEs 120).

Itinerary information may be static or dynamic. For instance, in someembodiments only static information such as an origin, destination,expected departure time, and/or expected arrival time may be provided.As another example, a carrier may provide dynamic itinerary informationvia a live feed, where such a live feed may include information such asdeparture time, arrival time, shipment status, flight status, etc.,where such information is updated at regular intervals, based on someupdate criteria (e.g., a status change from on-time to delayed, a changein expected departure time, etc.), and/or based on other relevantfactors. As still another example, an itinerary may be predicted,estimated, or otherwise generated based on machine learning models andlimited or no itinerary information available. For instance UEs 120having a current location associated with a particular airport fiveminutes before noon on a Wednesday may be inferred to be departing on ascheduled flight that departs from that particular airport on Wednesdaysat noon.

Location or geographic information may include information related tolocation of UE 120. Such location information may be provided at variouslevels of granularity, as appropriate for a particular application,status, location tracking resource, etc. For instance, a location mayinclude specific longitudinal and latitudinal coordinates. As anotherexample, a location may include an airport, terminal, or aircraft. Insome embodiments, the location or geographic information may includegeofence information (e.g., geofence definitions and/or events).

Location information may be received from various appropriate resources.For instance, location information may be received from UE 120 (e.g., asdetermined by UE 120, such as by using GPS or other suitable techniquesperformed by UE 120). As another example, location information may bereceived from a carrier database or other carrier resource (e.g., adevice or system associated with a wireless network, which may determinethe location of UE 120 by a Mobility and Management Entity (“MME”),Access and Mobility Management Function (“AMF”), or other suitabledevice or system). Additionally, or alternatively, some embodiments mayinclude various beacons, sensors, readers, and/or other devices that areable to interact with UE 120. Such devices may include proximity sensorsthat are able to interact with UE 120 over a wireless channel and mayprovide an indication when UE 120 passes within a threshold proximity tothe proximity sensors (sometimes referred to as “geofencing”).

Airport information may include information related to various airports.Such airports may be associated with an origin, destination,intermediate stop, and/or region. Airport information may include anairport location, which may be specified as a set of longitudinal andlatitudinal coordinates, as a geofence center point and radius, and/orother appropriate information. Airport information may further includeinformation such as hours of operation, associated carriers or othertransport resources, potential origins or destinations, etc.

As further shown in FIG. 1, mode manager 110 may analyze the collectedinformation in order to generate one or more communication mode triggersto be applied to UE 120. Such communication mode triggers may includevarious parameters, depending on the available information. Forinstance, if only a departure city is specified, the communication modetriggers may specify a condition that the trigger is met when UE 120 islocated within a threshold distance of an airport in the city. Forexample, the trigger may include geofence areas associated with eachairport in the city.

As another example, if a live feed of itinerary information (e.g., whichmay indicate progress along a travel route) is available, mode manager110 and/or UE 120 may update trigger definitions at regular intervals,based on some specified update criteria, and/or under other appropriateconditions. For instance, mode manager 110 and/or UE 120 may receiveitinerary information from a carrier resource, such as a server, wherethe received itinerary information may include a specific terminal oraircraft location, expected arrival and/or departure times, expectedtransit time, etc. As one example, a trigger definition associated witha departure event may be updated such that an area or locationassociated with the trigger definition is narrowed to reflect the morespecific information (e.g., the trigger definition may be associatedwith the plane or terminal location rather than a location of theairport). As another example, if the received itinerary informationincludes an updated departure time, the trigger may be updated toreflect the updated time. As still another example, mode manager 110and/or UE 120 may receive weather information from an online resourceand may update trigger definitions based on the received information(e.g., by increasing an expected time in transit and arrival time basedon an increase in predicted headwind speed).

A trigger may include multiple conditions (e.g., an origin location anda departure time). Mode manager 110 may send a configuration message toUE 120 including the trigger information. The trigger definition mayinclude various different elements associated with various differentsensors and/or measurement capabilities of UE 120. For instance, thetrigger definition may include UE sensor data associated with takeoffinformation such as data associated with an accelerometer, speedometer,barometer, altimeter, user interface (“UI”) elements, and/or othersuitable sensors (e.g., a microphone or camera). For instance, audiodata collected via a microphone of UE 120 may be compared to a triggerincluding a sonic profile associated with engine noise, such thatvarious operating conditions, events, and/or other information may bederived from the collected audio data (e.g., a sonic profile associatedwith taxiing, a sonic profile associated with a takeoff event, etc.). Asanother example, a trigger definition may include events based on inputsreceived via various UI elements. For instance, a user may use agraphical UI or keyboard to manually enable or disable the communicationmode feature.

In some embodiments, the triggers may be monitored at mode manager 110and/or UE 120. For example, mode manager 110 may provide (or may haveprovided) one or more triggers to UE 120. Based on these triggers, UE120 may monitor its location, information from one or more sensors of UE120, a received itinerary associated with UE 120, or other suitableinformation, to determine whether a given trigger is met. A giventrigger may be “met” when sensor data, monitored or determined by UE120, matches one or more sensor data profiles associated with thetrigger. In some embodiments, the monitored sensor data may “match” asensor data profile associated with the trigger when the monitoredsensor data exactly matches the sensor data profile. In someembodiments, a suitable similarity or correlation analysis may beperformed to determine whether a measure of similarity, between themonitored sensor data and the sensor data profile, exceeds a thresholdmeasure of similarity.

In some embodiments, mode manager 110 and UE 120 may communicate acrossvarious networks (e.g., wireless, cellular, etc.) in order to identifytrigger events associated with UE 120. For example, mode manager 110 mayreceive an itinerary associated with UE 120 from an external source(e.g., a source other than UE 120), indicating that UE 120 is scheduledto be located on an aircraft that is departing from a particular city ata particular time, and may receive location information from UE 120 atthe particular time indicating that UE 120 is located at an airport inthe particular city. In this instance, mode manager 110 may determinethat this trigger is met, and that UE 120 should disable its wirelesscommunication features. As described below, mode manager 110 may alsoindicate a duration for which UE 120 should disable its wirelesscommunication features (e.g., a scheduled flight duration, as indicatedby the itinerary), after which UE 120 may be configured to automaticallyenable its wireless communication features without further instruction.

If a communication mode trigger event is identified, UE 120 may disableits communications (e.g., operate in airplane mode, as indicated by icon130). During airplane mode operation, modules, features, circuitry, etc.related to wireless communications to and/or from UE 120 may bedisabled, powered down, deactivated, etc. Such modules, features, etc.may include location services. Thus, as briefly referred to above, UE120 may monitor local device resources or other information in order toidentify an airplane mode exit event.

After disabling communications, UE 120 may detect additional triggers,such as aircraft takeoff events, using various UE sensors. An aircrafttakeoff event (or, simply, a “takeoff event”) may refer to an instanceof an aircraft taking off from or departing an airport, airfield,landing strip, etc. In some embodiments, if communications are disabledbased on identification of a communication mode trigger event, anadditional trigger may be specified time threshold (e.g., alocation-based communication mode trigger may be followed by a takeoffevent within a specified time). An exit event definition may includedetection of an aircraft landing event. An aircraft landing event (or,simply, a “landing event”) may refer to an instance of an aircraftlanding at an airport, airfield, landing strip, etc., such as aftercompleting a flight.

Accelerometer data available locally at UE 120 may be monitored toidentify the takeoff event and the landing event, as the motion profilesassociated with such events may be distinctive relative to othersituations or conditions (e.g., transit via ship, truck, etc.). Takeoffand/or landing events may include, for instance, a minimum specifiedacceleration (or deceleration) threshold, minimum specified duration ofacceleration exceeding the specified threshold, calculated initial orfinal speed based on measured acceleration data, etc.

As another example, if an expected transport time was received by UE 120(e.g., as part of an itinerary, included in an update message from modemanager 110, etc.), an exit event definition may include a specifiedtransit duration such that UE 120 may wait the specified transitduration (e.g., the expected transport time plus a buffer time) beforeexiting airplane mode 130. The buffer time may be based on variousrelevant factors. For instance, a percentage or fraction of the totalexpected transit time may be added to the buffer time to account forroutine delays, changes in weather, etc. The buffer time may includeelements associated with an origin and/or destination. For instance,machine learning analysis may generate airport-specific expecteddeviations based on previous flight data associated with the originand/or destination airport, and such airport-specific deviations may beincluded in the buffer time. For example, if flights to a particulardestination airport (e.g., during a particular time of day, day of week,season, etc.) typically experience delays (which may be due to, forexample, recurring weather conditions such as fog or snow), theparticular destination airport may be associated with a buffer time thatis determined based on delays experienced by past flights (e.g., anaverage delay, median delay, etc.). The buffer time may include elementsrelated to various other attributes or factors. Such attributes and/orfactors may include, for instance, carrier performance history, aircrafttype, expected departure time (e.g., increased delays may be associatedwith a particular time of day), expected arrival time, aircraft loadrelative to capacity, and/or weather conditions.

If an exit trigger is identified, UE 120 may exit airplane mode 130 andmay activate wireless communication services such as location trackingand radio communication (e.g., voice and/or data services). Upon suchreactivation, UE 120 may interact with mode manager 110 to provideupdated location information and/or shipment status, receive updated oradditional trigger definitions, etc.

Some embodiments may store information related to identified events andapply machine learning to refine trigger definition and eventidentification. For instance, if a wireless communication modedeactivation trigger event is identified based on location (e.g., GPSdata indicating proximity to an airport), but a user manually overridesthe trigger event (e.g., by re-enabling wireless communications), themachine learning model may be updated to reflect that wirelesscommunications should not be deactivated under the specifiedcircumstances (e.g., by updating the trigger definition to have a closerproximity to the trigger location).

As another example of feedback that may be utilized to refine themachine learning model, if UE 120 erroneously identifies an exit triggerevent and enables wireless communication features based on the erroneousidentification of the exit trigger event, and UE 120 determines, afteractivating such wireless communication features (e.g., GPS features),that the exit trigger was erroneous, UE 120 may re-enter airplane modeand send feedback associated with the erroneous identification whencommunication is enabled (e.g., upon detection of a subsequent exitevent trigger). For instance, UE 120 may retrieve altimeter data todetermine that a current elevation above sea level does not match theexpected elevation at a destination airport (e.g., a measured elevationof 10,000 feet above sea level when a destination airport indicated inthe itinerary has a specified elevation of 100 feet above sea level). Asanother example, accelerometer data may be compared to a vibrationprofile indicating air travel, where accelerometer data that matches(e.g., within a threshold similarity, using a suitable similarityanalysis) a vibration profile indicating air travel may indicate that UE120 has erroneously detected an exit event. As still another example, ifUE 120 determines that wireless signals such as voice and/or dataservices are not available (e.g., a wireless network is not reachable)when airplane mode is disabled, an erroneous exit event may beidentified.

As another example, UE 120 may identify a particular airplane modetrigger event (e.g., a landing event that is associated with a landingof an aircraft on which UE 120 is located) based on a particular motion“profile” or “signature” (referred to herein as an “motion profile”)associated with sensor readings taken by one or more sensors of UE 120.The one or more sensor readings may be motion sensor readings taken byone or more motion sensors of UE 120. Such “motion sensors” may includevarious elements that are able to detect motion, location, and/orotherwise measure the environment of UE 120 to identify events such astakeoff and/or landing events. Such motion sensors may include, forinstance, accelerometers, speedometers, gyroscopes, pressure sensors,GPS sensors, global navigation satellite system (“GNSS”) sensors,altimeters, and/or other type of sensor that detects or measures motion.A motion profile may include an altitude profile that defines takeoffand/or landing events based on altitude information received from thelocal sensors of UE 120. A motion profile may include a set of motionsensor readings within a given duration of time.

For example, a particular motion profile may include one hundred sensorreadings taken within one second by an accelerometer of UE 120. Suchmotion profiles may be associated with takeoff events, landing events,taxi events, cruising events, and/or other types of events or statesassociated with transport or travel. Mode manager 110 may apply machinelearning to collected acceleration data (and/or other appropriate sensordata collected at UE 120) and data regarding takeoff, landing, and/orother such events in order to generate motion profiles. Such profilesmay be associated with specific UEs 120, UE types, aircraft or aircrafttype, airports (e.g., profiles may be associated with specific runways),weather conditions, time of day, flight path, and/or other appropriateresources or conditions.

UE 120 may activate wireless communications based on matching of currentsensor data collected at UE 120 to a motion profile and thus identify alanding event. If, upon activation of wireless communication features,sensor data indicates UE 120 is still airborne (e.g., the exit event wasdetected erroneously), the machine learning model may be updated toreflect that wireless communications should not be activated based onsuch a motion profile (and wireless communications may be deactivated).

As still another example, UE 120 may identify a takeoff event based onacceleration data measured at local sensors of UE 120. UE 120 mayprovide, upon activation of wireless communication features, feedback tomode manager 110 indicating the measured data associated with theidentified takeoff event (e.g., accelerometer data). In addition to suchdata received from UE 120, mode manager 110 may receive, for instance,data indicating aircraft location, where such data may be received froma resource such as a carrier server. Analysis of aircraft location mayindicate that the identified takeoff event was erroneous (i.e., theaircraft was still grounded at the time of the erroneously identifiedevent, and/or that the aircraft has not moved within a threshold periodof time after the potential takeoff event was identified), the machinelearning model may be updated such that a takeoff event is notidentified based on the measured acceleration data, and/or informationcorrelating the measured acceleration data to a takeoff event may bemodified (e.g., weighted less heavily). A similar approach may beapplied to landing events and activation of wireless communications.

As another example of machine learning, UE 120 may identify partialsatisfaction of a trigger definition (e.g., a proximity thresholdrelative to an airport) and may further analyze UE 120 information suchas location or accelerometer information. If analysis of UE 120 locationor accelerometer data indicates that UE 120 is stationary (indicating,for instance, that UE 120 is in a cargo hold of an aircraft), themachine learning model may indicate that UE 120 is more likely toexperience a takeoff event the longer UE 120 is stationary and mayupdate a communication mode trigger definition such that wirelesscommunication is more likely to be disabled the longer the aircraft isstationary. Thus, for instance, a trigger definition that includes adeparture time may be updated to account for an earlier departure if UE120 is stationary for longer than a threshold duration.

As another example, itinerary information may be estimated or predictedbased on location information associated with UE 120. For instance, UE120 may be determined to be at a location associated with a particularairport gate (e.g., within fifteen meters of the gate). Flightinformation may be retrieved based on information associated with a nextscheduled departure from the particular gate and a communication modetrigger event may be identified if the scheduled departure is within aparticular time threshold (e.g., thirty minutes). As another example, ifUE 120 is determined to be located within a geofence associated with anairport, mode manager 110 may retrieve flight information for the nextavailable flights from the airport to a destination associated with UE120 (if available), or the next flights to any destination (if nodestination information is associated with UE 120).

As still another example, a carrier may have a facility located near aparticular airport. Trucks or other vehicles associated with the carriermay travel back and forth from the facility to the particular airportalong a defined route. If UE 120 is identified as travelling along sucha defined route, a communication mode trigger may be updated such thatwireless communication is deactivated upon reaching a gate or otherterminal location associated with the carrier.

UE 120 may receive trigger updates from local resources (e.g., a UE 120associated with a carrier, aircraft, airport, etc.). For instance, acarrier may provide updated trigger information to UE 120 across a localwired or wireless channel. For instance, as a package with associated UE120 is loaded onto an aircraft, an update message including expecteddeparture time, arrival time, etc. may be delivered to UE 120 over thelocal channel. Similarly, as the package is loaded onto the aircraft, agraphic code, RFID, or other identifying information associated with thepackage may be scanned or otherwise retrieved and updated carrierinformation may be sent to mode manager 110 (e.g., expected departureand arrival times for the package). Mode manager 110 may send updatedtrigger information to UE 120 based on the carrier update.

FIG. 2 illustrates an example environment 200 in which one or moreembodiments, described herein, may be implemented. As shown, environment200 may include one or more mode managers 110, UEs 120, map resources210, carrier resources 220, one or more web resources 230, and network240. The quantity of devices and/or networks, illustrated in FIG. 2, isprovided for explanatory purposes only. In practice, environment 200 mayinclude additional devices and/or networks; fewer devices and/ornetworks; different devices and/or networks; or differently arrangeddevices and/or networks than illustrated in FIG. 2. For example, whilenot shown, environment 200 may include devices that facilitate or enablecommunication between various components shown in environment 200, suchas routers, modems, gateways, switches, hubs, etc. Alternatively, oradditionally, one or more of the devices of environment 200 may performone or more functions described as being performed by another one ormore of the devices of environments 200. Devices of environment 200 mayinterconnect with each other and/or other devices via wired connections,wireless connections, or a combination of wired and wirelessconnections. In some implementations, one or more devices of environment200 may be physically integrated in, and/or may be physically attachedto, one or more other devices of environment 200.

Mode manager 110 may include one or more devices (e.g., a server deviceor a distributed set of devices, such as a cloud computing system) thatperform one or more actions described herein. In some embodiments,portions of the functionality described below with respect to modemanager 110 may be implemented by UE 120. Mode manager 110 may manageinformation requests from UEs 120, distribute trigger definitions to UEs120, refine machine learning models, and receive information from othersystem resources 210-230.

In some embodiments, mode manager 110 may include a location managementmodule that may track UE 120 location. Such location tracking mayinclude receiving location information from UE 120. In some embodiments,mode manager 110 may communicate with various proximity sensorsstrategically positioned at various appropriate locations (e.g., areasassociated with airports, such as departure gates, areas associated withcarrier resources such as sorting facilities, and/or other appropriatelocations), in order to determine a location of UE 120.

UE 120 may include any computation and communication device that iscapable of communicating with one or more networks (e.g., network 240).For example, UE 120 may include a device that tracks locationinformation and environmental data associated with UE 120. UE 120 mayalso receive user interactions (e.g., voice input, touches on atouchscreen, “clicks” via an input device such as a mouse, etc.). Insome implementations, UE 120 may be, or may include, a radiotelephone, apersonal communications system (“PCS”) terminal (e.g., a device thatcombines a cellular radiotelephone with data processing and datacommunications capabilities), a personal digital assistant (“PDA”)(e.g., a device that includes a radiotelephone, a pager, etc.), a smartphone, a laptop computer, a tablet computer, a camera, a television, apersonal gaming system, a wearable device, and/or another type ofcomputation and communication device.

In some embodiments, UE 120 may be an asset tracker (“AT”) or otherInternet of things (IoT) device that may be used by shipment managementor logistics systems to monitor asset location, status, etc. ATs may becoupled to, embedded into, and/or otherwise associated with variouscontainers, packaging, housings, and/or other appropriate features ofvarious assets. Such assets may include, for instance, goods in transitor expected to be in transit. Processes and features described hereinmay allow such IoT devices, ATs, and/or other UEs 120 to comply withrules or regulations that require communications to be disabled while intransit (e.g., use of airplane mode when travelling by aircraft). Suchprogrammatic or automatic disabling of communications features while intransit may allow vendors, manufacturers, and/or other parties involvedin the transit of such devices to be in compliance with such rules orregulations, without needing to manually disable or power down thesedevices.

Map resources 210 may include one or more devices (e.g., a server deviceor a distributed set of devices, such as a cloud computing system) thatperform one or more actions described herein. For example, map resources210 may store and provide information regarding airport locations,carrier facility locations, etc. In some embodiments, map resources 210may be, or may include, public website, services, or other externalsystems.

Carrier resources 220 may include one or more devices (e.g., a serverdevice or a distributed set of devices, such as a cloud computingsystem) that perform one or more actions described herein. For example,carrier resources 220 may store and provide information regardingitinerary or shipment status, UE 120 location, etc. In some embodiments,carrier resources 220 may be, or may include, public website, services,or other external systems.

Web resources 230 may include one or more devices (e.g., a server deviceor a distributed set of devices, such as a cloud computing system) thatprovide information to UE 120 and/or mode manager 110 via network 240.Each of the web resources 230 may be associated with an informationresource (e.g., airport information, weather, etc.).

Network 240 may include one or more radio access networks (“RANs”), viawhich mode managers 110 and/or UEs 120 may access one or more othernetworks or devices, a core network of a wireless telecommunicationsnetwork, an IP-based packet data network (“PDN”), a wide area network(“WAN”) such as the Internet, a private enterprise network, and/or oneor more other networks. In some implementations, network 240 may be,include, or be in communication with a cellular network, such as aSecond Generation (2G) Global System for Mobile Communications(GSM)/Enhanced Data rate for GSM Evolution (EDGE) network, a ThirdGeneration (“3G”) network, a Fourth Generation (“4G”) Long-TermEvolution (“LTE”) network, a Fifth Generation (“5G”) network, a CodeDivision Multiple Access (“CDMA”) network, etc. UE 120 may connect to,and/or otherwise communicate with, via network 240, data servers,application servers, other UEs 120, etc. Network 240 may be connectedto, and/or otherwise in communication with, one or more other networks,such as a public switched telephone network (“PSTN”), a public landmobile network (“PLMN”), and/or another network.

FIG. 3 illustrates an example process 300 by which communication modetriggers may be generated based on itinerary information. As describedherein, such communication mode triggers may include a set of conditionsto be satisfied before disabling and/or enabling wireless communicationfeatures of UE 120. Process 300 may be performed when a UE 120 ispowered on, when a client application of some embodiments is launched,and/or at other appropriate times. In some embodiments, process 300 maybe performed by mode manager 110. In some embodiments, process 300 maybe performed by one or more other devices in addition to, or in lieu of,mode manager 110. Furthermore, in some embodiments a complementaryprocess may be performed by other devices, such as UE 120, map resource210, carrier resource 220, and/or web resource 230.

As shown, process 300 may include receiving (at 310) itineraryinformation. Itinerary information may include, for instance,information related to a carrier, origin, destination, departure time,arrival time, and/or other relevant information. Such information may beretrieved from various appropriate resources. For instance, user inputsmay be received at UE 120, where such user inputs may includeinformation such as an origin and/or destination. As another example,itinerary information may be retrieved from a resource such as a carrierresource 220, based upon identifying information such as a trackingnumber associated with UE 120.

Process 300 may include determining (at 320) whether a departurelocation has been specified. If the process determines (at 320) that nodeparture location has been specified, the process may retrieve (at 330)a list of locations based on proximity. If the process determines (at320) that a departure location has been specified, the process mayreceive (at 340) an itinerary status. Such a determination may be made(at 320) by evaluating the received itinerary information. A departurelocation may be specified in various appropriate ways, at various levelsof granularity (e.g., the departure location may include a specificairport, a city, a “from” address, and/or other appropriateinformation).

If the process determines (at 320) that no departure location has beenspecified, the process may retrieve (at 330) a list of locations basedon proximity. The list of locations may be retrieved from a resourcesuch as map resource 210. The list of locations may include locationsidentified based on proximity to UE 120 (e.g., a current location of UE120), proximity to a specified origin location, and/or proximity toother appropriate landmarks or locations (e.g., a carrier processingfacility).

Process 300 may include receiving (at 340) itinerary status, ifavailable. Such status information may be received from a resource suchas carrier resource 220. Itinerary status information may indicatewhether a live feed or other regularly updated information associatedwith an itinerary is available.

The process may include receiving (at 350) device status from one ormore UEs 120. Such device status may include, for instance, a currentlocation of the device, most recent movement or other identified event,available resources or connectivity, and/or other relevant information.For instance, mode manager 110 may receive a message from UE 120indicating current battery charge level, available network connections,and current location.

Process 360 may include selecting (at 360) a mode control algorithmbased on the received itinerary information, itinerary status, and/ordevice status. Such mode control algorithms may include, for instance, adirect cloud control (“DCC”) algorithm, a cloud adjustment control(“CAC”) algorithm, and a predictive location control (“PLC”) algorithm.The control mode algorithms will be described in more detail below.

The PLC algorithm may be selected when no itinerary information or onlylimited information is available. In PLC mode, any nearby airportlocation may be retrieved and included in a communication mode triggerdefinition. Utilizing the current location information provided by UE120, mode manager 110 may compare a location of UE 120 to a local map.If the location of UE 120 is within a proximity of a commercial airport,airplane mode may be automatically enabled. After airplane mode isenabled, UE 120 may periodically monitor whether the UE 120 is airborneutilizing data from local sensors without enabling wirelesscommunication features. If UE 120 determines that the location of UE 120is not airborne within some specified limit criteria (e.g., after anelapsed time and/or number of evaluations), the radio and GPS featuresmay be enabled in order to provide a current location to mode manager110. The current location may be compared to the local map data todetermine if UE 120 has left the vicinity of the candidate airport. Ifthe location of UE 120 is still within the vicinity of the airport, UE120 and/or mode manager 110 may determine that the airplane is waitingfor takeoff and a UE 120 may disable wireless communication features. IfUE 120 is determined to be airborne, UE 120 may periodically monitorlocal sensor data in order to identify a landing and enable wirelesscommunications after identifying such a landing. Such an airportdetection cycle may continue until a user terminates or disables thecommunication mode feature or if target shipment destination has beenprovided, the communication mode feature may be disabled automaticallyif UE 120 is determined to be within the vicinity of the targetdestination.

The CAC algorithm may be selected when some itinerary information isavailable (e.g., a third-party carrier tracking number may specify anorigin and/or destination). In CAC mode, the list of candidate airportsmay be reduced versus operation in PLC mode, allowing for reducedfrequency of deactivating communication features by reducing the numberof candidate airports as compared to the number of candidate airportsidentified in PLC mode. Such reduction in deactivation frequency mayreduce device power consumption and allow for additional collectionand/or communication of data including UE location, sensor data, etc.while the communication features of UE 120 are enabled.

The CAC algorithm may require that an origin, target destination, and3^(rd) party source for additional shipment information (e.g.: UPStracking info) have been provided. Utilizing the shipment routeinformation (e.g., as provided by a user and 3^(rd) party source), afiltered target airport list may be generated. The list may be used tosetup one or more UE GeoFence alarms. Mode manager 110 may activate thecommunication mode feature when a GeoFence alarm is triggered. If the3^(rd) party tracking source provides detailed flight or other itineraryinformation (e.g., departure and/or arrival time), the activation of thecommunication mode feature may be optimized based on the itineraryinformation in addition to the location information. Mode manager 110may schedule UE 120 to check for landing information periodically ifspecific itinerary information is not available.

The DCC algorithm may be selected when full access to itineraryinformation such as shipment and flight schedule is available and mayfurther reduce communication frequency with real-time updates. In DCCmode, trigger information may be defined with relatively highspecificity, based on real-time or near real-time information related tothe itinerary, thus further reducing deactivation frequency and/orduration.

The DCC algorithm may require specific information relevant to theitinerary associated with a UE 120. Utilizing the shipment targetdestination, starting destination, scheduled flight start and landinginfo, UE 120 and/or mode manager 110 may generate a list of “expected”flight take-off and landing times. The mode manager 110 may schedule UE120 to enable the communication mode feature and check for airplanelanding based on the provided time(s).

Process 300 may include sending (at 370) a configuration message to oneor more UEs 120. Such a configuration message may include, for instance,a list of airport locations, an estimated departure time, estimatedarrival time, flight or carrier information, a mode control selection orindication, trigger definitions, and/or other appropriate information.

The process may store (at 380) the configuration data associated with aparticular UE 120. Such data may be utilized for machine learninganalysis (e.g., by evaluating the accuracy of predicted versus actualdata for a particular UE 120).

FIG. 4 illustrates an example process 400 by which UE information ismonitored and compared to communication mode triggers to identifytrigger events. As described herein, trigger event identification may beutilized to enable and/or disable wireless communications. Process 400may be performed when UE 120 is powered on, when a client application ofsome embodiments is executed, and/or at other appropriate times. In someembodiments, process 400 may be performed by UE 120. In someembodiments, process 400 may be performed by one or more other devicesin addition to, or in lieu of, UE 120. Furthermore, in some embodimentsa complementary process may be performed by other devices, such as modemanager 110.

As shown, process 400 may include enabling (at 410) a communication modefeature. Such a feature may be implemented at UE 120 such that UE mayautomatically disable and/or enable wireless communication based oncommunication mode triggers and/or exit event triggers as describedabove.

Process 400 may include defining (at 420) one or more communication modetriggers. Such trigger definitions may include various elements, such asan origin, destination, departure time, etc.

Process 400 may include receiving (at 430) location data at UE 120. Suchlocation data may be received from local resources (e.g., a GPS moduleof UE 120), and/or external resources. For example, mode manager 110 maymonitor a location of UE 120 based on information received from UE 120,other appropriate resources such as local proximity sensors of someembodiments, and/or web resources 230 and/or carrier resource 220 viaNetwork 240.

Process 400 may include receiving (at 440) sensor data at UE 120. Suchsensor data may include, for instance, accelerometer data received fromone or more accelerometers associated with UE 120. Such sensor data mayinclude location or position information related to UE 120.

Process 400 may include comparing (at 450) UE 120 sensor and/or locationdata to the various communication mode triggers defined at 420. Process400 may include determining (at 460) whether a trigger event has beenidentified. Such a determination may be based on the comparison of UE120 sensor and/or location data to the various trigger definitions.

As described above, a trigger event may include a location and/orproximity to the location. If UE 120 sensor and/or location dataindicates that UE 120 is within the specified proximity to the specifiedlocation, a trigger event may be identified. As described above, thetrigger event may include multiple conditions that must be satisfied inorder for a trigger to be identified. For instance, a trigger definitionmay include a proximity to a location and a departure time window, wherethe UE 120 location must be within the specified proximity to thelocation during the departure time window in order for a trigger to beidentified.

In some embodiments, if no trigger event is identified (at 460—NO)within a specified timeout period, process 400 may include disabling thecommunication mode feature enabled at 410. UE 120 may update itineraryinformation and/or communication mode configuration information using aprocess such as process 300 if the communication mode feature isdisabled.

Process 400 may include determining (at 470) whether live information isavailable. If the process determines that live or real-time itineraryinformation is available (at 470—YES), the process receive such updatedinformation and may update (at 420) communication mode triggerdefinitions based on the updated itinerary information and mayiteratively perform elements 420-470 until a trigger is identified (at460—YES). Updated itinerary information may be received from a resourcesuch as carrier resource 220 and/or web resource 230.

If the process determines (at 470—NO) that live information is notavailable, the process may iteratively receive (at 430) location data atUE 120, receive (at 440) sensor data at UE 120, compare (at 450) UE datato trigger definitions, and determine (at 460) whether a trigger eventhas been identified until a trigger event is identified (at 460—YES) orsome other criteria is satisfied (e.g., a timeout period is reached oran abort event is identified).

If a trigger is identified (at 460—YES), process 400 may disable (at480) wireless communications and may monitor local sensor information inorder to identify an exit trigger. UE 120 may monitor local informationusing a process such as process 500 described below.

FIG. 5 illustrates an example process 500 by which UE information ismonitored locally when wireless communications are disabled and comparedto communication mode exit triggers to identify exit trigger events. Asdescribed herein, exit trigger events may be used to enable wirelesscommunications. Process 500 may be performed when wireless communicationis disabled and/or at other appropriate times. In some embodiments,process 500 may be performed by UE 120. In some embodiments, process 500may be performed by one or more other devices in addition to, or in lieuof, UE 120. Furthermore, in some embodiments a complementary process maybe performed by other devices, such as mode manager 110.

As shown, process 500 may include receiving sensor data at UE 120. Suchsensor data may be received from sensors associated with UE 120. Suchsensors may include, for instance, accelerometers, gyroscopes,speedometers, altimeters, barometers, temperature sensors, hygrometers,and/or various other sensors that are able to measure various parameterswithout use of communication features of UE 120.

In some embodiments, the data received (at 510) may include event datareceived from local peripheral devices associated with UE 120. Suchlocal peripheral devices may include, for instance, one or more UIinputs, keyboards, wired sensors, and/or various other device that areable to measure various parameters and/or generate event notificationswithout use of wireless communication features of UE 120.

Process 500 may include determining (at 520) whether an exit triggerevent has been identified. Such events may be identified by comparing UE120 information such as sensor information to one or more exit triggerdefinitions. As discussed above, in some embodiments an exit trigger mayinclude a takeoff event and a landing event. Such events may beidentified by comparing acceleration or positioning data, for instance,to some evaluation criteria.

If no exit event is identified, the process may continue to receive (at510) sensor and/or event data and determine (at 520) whether an exitevent has been identified based on the received data until the processdetermines that an exit event has been identified. The exit triggerevent may include a transit time duration limit (e.g., if a takeoffevent is identified and no landing event is identified within thetransit time duration limit, an exit trigger may be identified),initialization time limit (e.g., if no takeoff event is identifiedwithin a specified time limit of enabling the communication modefeature, some embodiments may identify an exit trigger event), and/orother appropriate timeout or other exit triggers.

If process 500 determines that an exit event has been identified (at520), the process may enable (at 530) wireless communications features.Process 500 may include receiving (at 540) location data at UE 120. Suchlocation data may be received from local resources (e.g., a GPS moduleof UE 120, external resources or sensors associated with UE 120, etc.)and/or from external resources (e.g., mode manager 110).

Process 500 may send (at 550) an update to mode manager 110. Such anupdate may include information such as location of the UE 120, UE statusinformation, event trigger information, and/or other relevantinformation. Process 500 may include receiving (at 560) a configurationmessage from mode manager 110. Such a configuration message may includeinformation such as sensor information, updated trigger conditions ordefinitions, itinerary status or live feed information, updated machinelearning models, mode control algorithm selections, and/or otherrelevant information.

The process may determine (at 570) whether the final destination hasbeen reached. Such a determination may be made by comparing a currentlocation to a final location, based on itinerary information associatedwith UE 120.

If the process determines that the final destination has not beenreached, the process may define or update (at 420) one or morecommunication mode triggers and further execute process 400 as describedabove.

If the process determines that the final destination has been reached(at 570), the process may update (at 580) the communication mode featuresuch that communication features of UE 120 are enabled without regardfor matching of any trigger definition. Thus, for instance, UE 120 maybe at a location within an area associated with an airport withoutcausing communication features to be deactivated.

FIG. 6 illustrates an example process 600 by which machine learning isapplied to event history and used to update event trigger definitions.Process 600 may be performed when a trigger event is identified, when aUE 120 reaches a final destination, and/or at other appropriate times.In some embodiments, process 600 may be performed by mode manager 110.In some embodiments, process 600 may be performed by one or more otherdevices in addition to, or in lieu of, mode manager 110. Furthermore, insome embodiments a complementary process may be performed by otherdevices, such as UE 120 or carrier resource 220.

As shown, process 600 may include receiving (at 610) event history. Suchevent history may be received from a storage or other resourceaccessible to mode manager 110. Event information including UE sensordata, event time(s), trigger definitions, etc. may be received by modemanager 110 from UEs 120. The event information may be stored by modemanager 110, UE 120, and/or other appropriate resources.

Process 600 may include receiving (at 620) event trigger definitioninformation. Such event trigger definition information may include, forinstance, mode control algorithm selected, condition definitions, etc.

The process may receive (at 630) itinerary data. Such itinerary data mayinclude carrier or other third-party data, user feedback, and/or otherappropriate information that may be related to trigger event definitionor analysis. Itinerary data may include information such as departurelocation, arrival location, departure time, arrival time, statusinformation, aircraft type and/or status, and/or other relevantitinerary information available from carrier resource 220. Otherthird-party data may include map data received from map resource 210and/or other data received from web resources 230 (e.g., weatherinformation).

Process 600 may include analyzing (at 640) the received data to refinemachine learning models of some embodiments. Such analysis may include,for instance, comparison of sensor or other information collected at UE120 while communications are disabled to transmit data indicatingdeparture and/or arrival location, time, etc., as determined by aresource such as carrier resource 220.

FIG. 7 illustrates example components of device 700. One or more of thedevices described above may include one or more devices 700. Device 700may include bus 710, processor 720, memory 730, input component 740,output component 750, and communication interface 760. In anotherimplementation, device 700 may include additional, fewer, different, ordifferently arranged components.

Bus 710 may include one or more communication paths that permitcommunication among the components of device 700. Processor 720 mayinclude a processor, microprocessor, or processing logic that mayinterpret and execute instructions. Memory 730 may include any type ofdynamic storage device that may store information and instructions forexecution by processor 720, and/or any type of non-volatile storagedevice that may store information for use by processor 720.

Input component 740 may include a mechanism that permits an operator toinput information to device 700, such as a keyboard, a keypad, a button,a switch, etc. Output component 750 may include a mechanism that outputsinformation to the operator, such as a display, a speaker, one or morelight emitting diodes (“LEDs”), etc.

Communication interface 760 may include any transceiver-like mechanismthat enables device 700 to communicate with other devices and/orsystems. For example, communication interface 760 may include anEthernet interface, an optical interface, a coaxial interface, or thelike. Communication interface 760 may include a wireless communicationdevice, such as an infrared (“IR”) receiver, a Bluetooth® radio, a WiFiradio, a cellular radio, or the like. The wireless communication devicemay be coupled to an external device, such as a remote control, awireless keyboard, a mobile telephone, etc. In some embodiments, device700 may include more than one communication interface 760. For instance,device 700 may include an optical interface and an Ethernet interface.

Device 700 may perform certain operations relating to one or moreprocesses described above. Device 700 may perform these operations inresponse to processor 720 executing software instructions stored in acomputer-readable medium, such as memory 730. A computer-readable mediummay be defined as a non-transitory memory device. A memory device mayinclude space within a single physical memory device or spread acrossmultiple physical memory devices. The software instructions may be readinto memory 730 from another computer-readable medium or from anotherdevice. The software instructions stored in memory 730 may causeprocessor 720 to perform processes described herein. Alternatively,hardwired circuitry may be used in place of or in combination withsoftware instructions to implement processes described herein. Thus,implementations described herein are not limited to any specificcombination of hardware circuitry and software.

The foregoing description of implementations provides illustration anddescription but is not intended to be exhaustive or to limit thepossible implementations to the precise form disclosed. Modificationsand variations are possible in light of the above disclosure or may beacquired from practice of the implementations.

For example, while series of blocks have been described with regard toFIGS. 1 and 3-6, the order of the blocks may be modified in otherimplementations. Further, non-dependent blocks may be performed inparallel. Additionally, while the figures have been described in thecontext of particular devices performing particular acts, in practice,one or more other devices may perform some or all of these acts in lieuof, or in addition to, the above-mentioned devices.

The actual software code or specialized control hardware used toimplement an embodiment is not limiting of the embodiment. Thus, theoperation and behavior of the embodiment has been described withoutreference to the specific software code, it being understood thatsoftware and control hardware may be designed based on the descriptionherein.

Even though particular combinations of features are recited in theclaims and/or disclosed in the specification, these combinations are notintended to limit the disclosure of the possible implementations. Infact, many of these features may be combined in ways not specificallyrecited in the claims and/or disclosed in the specification. Althougheach dependent claim listed below may directly depend on only one otherclaim, the disclosure of the possible implementations includes eachdependent claim in combination with every other claim in the claim set.

Further, while certain connections or devices are shown, in practice,additional, fewer, or different, connections or devices may be used.Furthermore, while various devices and networks are shown separately, inpractice, the functionality of multiple devices may be performed by asingle device, or the functionality of one device may be performed bymultiple devices. Further, multiple ones of the illustrated networks maybe included in a single network, or a particular network may includemultiple networks. Further, while some devices are shown ascommunicating with a network, some such devices may be incorporated, inwhole or in part, as a part of the network.

Some implementations are described herein in conjunction withthresholds. To the extent that the term “greater than” (or similarterms) is used herein to describe a relationship of a value to athreshold, it is to be understood that the term “greater than or equalto” (or similar terms) could be similarly contemplated, even if notexplicitly stated. Similarly, to the extent that the term “less than”(or similar terms) is used herein to describe a relationship of a valueto a threshold, it is to be understood that the term “less than or equalto” (or similar terms) could be similarly contemplated, even if notexplicitly stated. Further, the term “satisfying,” when used in relationto a threshold, may refer to “being greater than a threshold,” “beinggreater than or equal to a threshold,” “being less than a threshold,”“being less than or equal to a threshold,” or other similar terms,depending on the appropriate context.

To the extent the aforementioned implementations collect, store, oremploy personal information provided by individuals, it should beunderstood that such information shall be collected, stored, and used inaccordance with all applicable laws concerning protection of personalinformation. Additionally, the collection, storage, and use of suchinformation may be subject to consent of the individual to such activity(for example, through “opt-in” or “opt-out” processes, as may beappropriate for the situation and type of information). Storage and useof personal information may be in an appropriately secure mannerreflective of the type of information, for example, through variousencryption and anonymization techniques for particularly sensitiveinformation.

No element, act, or instruction used in the present application shouldbe construed as critical or essential unless explicitly described assuch. An instance of the use of the term “and,” as used herein, does notnecessarily preclude the interpretation that the phrase “and/or” wasintended in that instance. Similarly, an instance of the use of the term“or,” as used herein, does not necessarily preclude the interpretationthat the phrase “and/or” was intended in that instance. Also, as usedherein, the article “a” is intended to include one or more items, andmay be used interchangeably with the phrase “one or more.” Where onlyone item is intended, the terms “one,” “single,” “only,” or similarlanguage is used. Further, the phrase “based on” is intended to mean“based, at least in part, on” unless explicitly stated otherwise.

What is claimed is:
 1. A device, comprising: one or more processorsconfigured to: identify one or more models that are based on sensor datareceived from a plurality of User Equipment (“UEs”), wherein the one ormore models associate one or more trigger conditions to one or more setsof the sensor data received from the plurality of UEs; receiveparticular sensor data associated with a particular UE; compare thereceived particular sensor data to the one or more sets of sensor dataassociated with the one or more models; identify, based on thecomparing, that a particular trigger condition, of the one or moretrigger conditions associated with the one or more models, has been met;and disable one or more wireless communication features associated withthe particular UE based on determining that the particular triggercondition has been met.
 2. The device of claim 1, wherein the one ormore processors are further configured to: generate or modify the one ormore models using one or more machine learning techniques.
 3. The deviceof claim 1, wherein the received particular sensor data includeslocation data indicating a location of the particular UE.
 4. The deviceof claim 1, wherein the received particular sensor data includes audiodata collected by the particular UE.
 5. The device of claim 4, whereinthe one or more sets of sensor data include one or more sonic profiles,wherein the one or more processors are further configured to: determine,based on the comparing, that the audio data matches a particular sonicprofile of the one or more sonic profiles.
 6. The device of claim 1,wherein the one or more wireless communication features are associatedwith communications between the particular UE and a wireless network,wherein the sensor data associated with the particular UE is associatedwith local device resources of the particular UE.
 7. The device of claim1, wherein the association between the one or more trigger conditionsand the one or more sets of sensor data are based on feedback receivedvia one or more UEs, of the plurality of UEs, after wirelesscommunication features of the one or more UEs were disabled based on theone or more trigger conditions.
 8. A non-transitory computer-readablemedium, storing a set of processor-executable instructions to: identifyone or more models that are based on sensor data received from aplurality of User Equipment (“UEs”), wherein the one or more modelsassociate one or more trigger conditions to one or more sets of thesensor data received from the plurality of UEs; receive particularsensor data associated with a particular UE; compare the receivedparticular sensor data to the one or more sets of sensor data associatedwith the one or more models; identify, based on the comparing, that aparticular trigger condition, of the one or more trigger conditionsassociated with the one or more models, has been met; and disable one ormore wireless communication features associated with the particular UEbased on determining that the particular trigger condition has been met.9. The non-transitory computer-readable medium of claim 8, wherein theplurality of processor-executable instructions further includeprocessor-executable instructions to: generate or modify the one or moremodels using one or more machine learning techniques.
 10. Thenon-transitory computer-readable medium of claim 8, wherein the receivedparticular sensor data includes location data indicating a location ofthe particular UE.
 11. The non-transitory computer-readable medium ofclaim 8, wherein the received particular sensor data includes audio datacollected by the particular UE.
 12. The non-transitory computer-readablemedium of claim 11, wherein the one or more sets of sensor data includeone or more sonic profiles, wherein the plurality ofprocessor-executable instructions further include processor-executableinstructions to: determine, based on the comparing, that the audio datamatches a particular sonic profile of the one or more sonic profiles.13. The non-transitory computer-readable medium of claim 8, wherein theone or more wireless communication features are associated withcommunications between the particular UE and a wireless network, whereinthe sensor data associated with the particular UE is associated withlocal device resources of the particular UE.
 14. The non-transitorycomputer-readable medium of claim 8, wherein the association between theone or more trigger conditions and the one or more sets of sensor dataare based on feedback received via one or more UEs, of the plurality ofUEs, after wireless communication features of the one or more UEs weredisabled based on the one or more trigger conditions.
 15. A method,comprising: identifying one or more models that are based on sensor datareceived from a plurality of User Equipment (“UEs”), wherein the one ormore models associate one or more trigger conditions to one or more setsof the sensor data received from the plurality of UEs; receivingparticular sensor data associated with a particular UE; comparing thereceived particular sensor data to the one or more sets of sensor dataassociated with the one or more models; identifying, based on thecomparing, that a particular trigger condition, of the one or moretrigger conditions associated with the one or more models, has been met;and disabling one or more wireless communication features associatedwith the particular UE based on determining that the particular triggercondition has been met.
 16. The method of claim 15, the method furthercomprising: generating or modifying the one or more models using one ormore machine learning techniques.
 17. The method of claim 15, whereinthe received particular sensor data includes location data indicating alocation of the particular UE.
 18. The method of claim 15, wherein thereceived particular sensor data includes audio data collected by theparticular UE, wherein the one or more sets of sensor data include oneor more sonic profiles, the method further comprising: determining,based on the comparing, that the audio data matches a particular sonicprofile of the one or more sonic profiles.
 19. The method of claim 15,wherein the one or more wireless communication features are associatedwith communications between the particular UE and a wireless network,wherein the sensor data associated with the particular UE is associatedwith local device resources of the particular UE.
 20. The method ofclaim 15, wherein the association between the one or more triggerconditions and the one or more sets of sensor data are based on feedbackreceived via one or more UEs, of the plurality of UEs, after wirelesscommunication features of the one or more UEs were disabled based on theone or more trigger conditions.